Terrain Classification from Body-mounted Cameras during Human Locomotion

Research output: Contribution to journalArticle (Academic Journal)

8 Citations (Scopus)
272 Downloads (Pure)

Abstract

This paper presents a novel algorithm for terrain type classification based on monocular video captured from the viewpoint of human locomotion. A texture-based algorithm is developed to classify the path ahead into multiple groups that can be used to support terrain classification. Gait is taken into account in two ways. Firstly, for key frame selection, when regions with homogeneous texture characteristics are updated, the frequency variations of the textured surface are analysed and used to adaptively define filter coefficients. Secondly, it is incorporated in the parameter estimation process where probabilities of path consistency are employed to improve terrain-type estimation. When tested with multiple classes that directly affect mobility a hard surface, a soft surface and an unwalkable area - our proposed method outperforms existing methods by up to 16%, and also provides improved robustness.
Original languageEnglish
Pages (from-to)2249-2260
Number of pages12
JournalIEEE Transactions on Cybernetics
Volume45
Issue number10
Early online date20 Nov 2014
DOIs
Publication statusPublished - Oct 2015

Keywords

  • Classification
  • recursive filter
  • terrain classification
  • texture

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    31/07/1231/07/15

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